Before we dive deep into building a few recommender systems using real-world data sets, we'll take a short detour and spend some time thinking about Big Data. Many real-world recommender systems arise out of the analysis of massive data sets. Examples include the product recommendation engine of amazon.com and the movie recommendation engine of Netflix.
Most, if not all, of the data sets that we have looked at in this book have been relatively small in size and have been chosen quite intentionally in order for the reader to be able to follow along with the examples and not have to worry about having access to powerful computing resources. These days, the field of predictive analytics, as well as the related fields of machine learning, data science, and data analysis in general, is heavily concerned with the importance of handling Big Data.
